DocumentCode :
419712
Title :
WillHunter: interactive image retrieval with multilevel relevance
Author :
Wu, Hong ; Lu, Hanqing ; Ma, Songde
Author_Institution :
Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., China
Volume :
2
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
1009
Abstract :
Relevance feedback has become a key component in CBIR system. Although most current relevance feedback approaches are based on dichotomous relevance measurement, this coarse measurement is a distortion of the reality. We study relevance feedback with multi-level relevance measurement to better identify the u ser needs and preferences. To validate the use of multi-level relevance measurement and our relevance feedback algorithm, we developed a CBIR prototype system - WillHunter. There are two novelties in our system, one is our SVM-based fast learning algorithm; another is the easy-to-use graphical user interface, especially the relevance-measuring instrument. Not only experiments are conducted to assess the algorithm, but also usability study is carried out to evaluate the user interface.
Keywords :
content-based retrieval; graphical user interfaces; image retrieval; relevance feedback; support vector machines; SVM-based fast learning algorithm; WillHunter; content-based image retrieval; dichotomous relevance measurement; graphical user interface; interactive image retrieval; relevance feedback; Current measurement; Distortion measurement; Feedback; Image retrieval; Information science; Instruments; Pattern recognition; Prototypes; Usability; User interfaces;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1334430
Filename :
1334430
Link To Document :
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